Design of an Automatic Control Algorithm for Energy-Efficient ...

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Optimiser code 168 real_T randn(real_T m, real_T s ) 644 / ∗ ======================================================================== ∗ Returns a normal (Gaussian) distributed real number . 646 ∗ NOTE: u s e s > 0 . 0 ∗ 648 ∗ Taken from ∗ Name : r v g s . c (Random Va riate GeneratorS) 650 ∗ Author : Steve Park & Dave Geyer ∗ Language : ANSI C 652 ∗ Latest Revision : 10 28 98 654 ∗ ∗ http://www.cs.wm.edu/~va/software/park/ ∗ Uses a very accurate approximation of the normal idf due to Odeh & Evans , 656 ∗ J. Applied Statistics , 1974, vol 23, pp 96 97. 658 ∗/ { ∗ ======================================================================== 660 const real_T p0 = 0.322232431088; const real_T q0 = 0.099348462606; const real_T p1 = 1.0; const real_T q1 = 0.588581570495; 662 const real_T p2 = 0.342242088547; const real_T q2 = 0.531103462366; const real_T p3 = 0.204231210245e 1; const real_T q3 = 0.103537752850; 664 const real_T p4 = 0.453642210148e 4; const real_T q4 = 0.385607006340e 2; 666 real_T u , t , p , q , z ; u = Random ( ) ; 668 if (u < 0.5) 670 else t = sqrt( 2.0 ∗ log(u)) ; t = sqrt( 2.0 ∗ log (1.0 u)) ; 672 p = p0 + t ∗ (p1 + t ∗ (p2 + t ∗ (p3 + t ∗ p4) ) ) ; q = q0 + t ∗ (q1 + t ∗ (q2 + t ∗ (q3 + t ∗ q4) ) ) ; 674 if (u < 0.5) 676 else z = (p / q) t; z = t (p / q) ; 678 return (m + s ∗ z ) ; 680 } real_T randu(real_T a , real_T b) 682 / ∗ =========================================================== ∗ Returns a uniformly distributed real number between a and b. 684 ∗ NOTE: u s e a andom Va riate GeneratorS) 688 ∗ Author : Steve Park & Dave Geyer ∗ Language : ANSI C
Optimiser code 169 690 ∗ Latest Revision : 10 28 98 692 ∗ 694 ∗/ { ∗ http://www.cs.wm.edu/~va/software/park/ ∗ =========================================================== 696 return (a + (b a ) ∗ Random ( ) ) ; 698 } 700 real_T Random( void) { / ∗ =========================================================== 702 ∗ Returns random value between 0 and 1.0. ∗ Uses internal rand() generator 704 ∗ =========================================================== ∗/ 706 return (real_T) rand () /RAND_MAX; 708 } 710 /∗ 712 ∗ 714 { 716 } void PlantSeeds(int_T x) ∗ Use this function to initialise the random number generator ∗/ srand ((unsigned)x) ;
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ISSN 0280-5316 ISRN LUTFD2/TFRT--58
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Diploma thesis subject Problem stat
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Acknowledgements ii Acknowledgement
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Acknowledgements iv 3.1.4 Windscree
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Acknowledgements vi 8.5 System simu
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Nomenclature viii Nomenclature Symb
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Nomenclature x Other symbols Symbol
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Nomenclature xii Subscript Descript
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1 Introduction Energy consumption t
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1 Introduction 3 adjustment of the
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2 Control objectives 5 2.1 Windscre
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2 Control objectives 7 2.2 Comfort
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2 Control objectives 9 � Metaboli
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2 Control objectives 11 ��
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2 Control objectives 13 Figure 2.6:
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2 Control objectives 15 2.4 Influen
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3 System description 17 or heat com
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3 System description 19 calculated
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3 System description 21 ��
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3 System description 23 � � �
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3 System description 25 defrost tem
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3 System description 27 Figure 3.4:
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3 System description 29 width modul
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3 System description 31 ��
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3 System description 33 shown in Fi
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3 System description 35 of performa
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4 Control strategy The main goal of
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4 Control strategy 39 limits are di
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4 Control strategy 41 ��
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4 Control strategy 43 cabin. This s
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4 Control strategy 45 controlled. T
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5 The disturbance estimator 47 in e
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6 The optimiser: an evolutionary al
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7 The HVAC-system controller 69 �
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7 The HVAC-system controller 71 7.5
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8 System and functionality integrat
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9 The MUTE project 95 order to fit
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10 Hardware and characteristics of
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11 Matlab implementation The climat
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11 Matlab implementation 111 Only r
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11 Matlab implementation 113 left i
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11 Matlab implementation 115 tion a
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Page 149 and 150: 13 Conclusion 129 13.2 Possible imp
Page 151 and 152: Bibliography [1] Holger Großmann.
Page 153 and 154: Bibliography 133 [22] M. Wang, T.M.
Page 155 and 156: Appendices
Page 157 and 158: B In- and outputs The interface bet
Page 159 and 160: Signal Unit Range Type Comment Stat
Page 161 and 162: In- and outputs 141 B.3 Error codes
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Page 165 and 166: Simulation parameters 145 C.2 Contr
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Page 169 and 170: Simulation parameters 149 C.5 Test
Page 171 and 172: Additional simulation results 151 D
Page 173 and 174: Optimiser code 153 real_T ∗panic_
Page 175 and 176: Optimiser code 155 52 return 10; 54
Page 177 and 178: Optimiser code 157 138 /∗ return
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Page 181 and 182: Optimiser code 161 ∗ IMEA_breedin
Page 183 and 184: Optimiser code 163 414 } 416 } } st
Page 185 and 186: Optimiser code 165 if (sortedPop [
Page 187: Optimiser code 167 596 ∗ Printout
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